Traditionally structure elucidation of a given organic compound, either synthesized or naturally occurring is assisted by NMR mainly 1H and 13Cspectroscopy. First step in a spectral analysis is to detect the characteristic structural fragments and their corresponding chemical shift values. Chemical shift provides NMR its diagnostic power to routinely reveal conformation and stereochemistry at the functional group level. It is indicative of the overall structure of a molecule and explains its exact electronic environment as well as its local geometry and hybridization thus encoding several properties of the molecule including protein binding. Chemical shifts also enable identification of the environment of a proton and reveal the steric, electronic and spatial arrangement of the neighboring atoms. The factors affecting chemical shift values include electron density around proton, electronegativity of neighboring groups, anisotropic induced magnetic fields. It is represented by δ (delta) and is usually mentioned as part per million, (ppm). FIGS. 15 and 16 depict the typical chemical shift values (in ppm) of proton and carbon NMR of the commonly known fragment space. A molecule can be theoretically disintegrated into its constituent fragments wherein each of the fragments corresponds to a peak in the entire NMR spectrum with fixed chemical shift values on the ppm scale. An illustration is shown in FIG. 1 where both carbon and proton NMR of an organic compound 1 and the corresponding peak assignments of its constituent fragments are highlighted.
Fragment based virtual screening methods are gaining precedence in Lead Identification (LI) and Lead Optimization (LO) phases of drug discovery processes. Virtual drug like molecules can be generated combinatorially from a fixed number of possible chemical structural fragments therefore pre-screening fragments for their goodness of fit instead of fully enumerated libraries seems a more efficient approach. Although fragments sample most of the relevant chemical space yet they leave scope for ligand optimization in terms of hydrophilicity, hydrophobicity, steric features etc. to enhance their drug-likeness. The fragment libraries are characterized by biophysical analytical techniques like IR (Infra Red), NMR and Mass Spectroscopy. Because of its sensitivity and capability to capture details of neighboring environment of an atom NMR spectroscopy is the frequently used technique for identifying fragments that bind to a target protein.
Apart from structural elucidation, NMR also finds extended application in functional characterization of fragments in a molecule when present in a biological system. Group specific enzymes act on molecules possessing specific functional groups. For instance hydrolases act on amide, peptide, ester groups, lyases on double bonds, carbon-oxygen (C—O), carbon-sulfur (C—S) bonds, demethylases on methyl groups etc. Each fragment component in a compound makes some contribution to the overall biological activity. NMR based methods have been exploited in the field of drug design and discovery in the past. SAR by NMR is a prevalent technique in drug discovery to understand ligand interactions with target using chemical shift mapping to screen low binding ligands. The known experimental techniques in NMR based high throughput screening are reporting screening, spin labels, 3-FABS (Three Fluorine Atoms for Biochemical Screening), LOGSY (Ligand Observation with Gradient Spectroscopy), affinity tags etc. The techniques are not restricted to soluble proteins but are also available for membrane proteins which are equally attractive pharmaceutical targets. There are excellent reviews devoted to their description complete with successful case studies. The limitations arise when the protein has a big size or it forms large multimers or there is a large solvent exposed binding site In addition to that the high cost of equipment, maintenance along with requirement of high concentration of samples required to detect weak binding makes fragment based identification a challenging task. Therefore an in-silico approach to screen molecular fragments would be a preferred option.
There are a number of ‘fragment based similarity’ searching methods available in literature to rank molecules in a database. Computationally it is carried out by using binary dataset which encode presence or absence of certain substructure fragments in a given query molecule and compare with similar such features in the database entries. For high speed screening structural keys are generally represented as Boolean arrays and bitmaps where each bit represents an absence or presence of a structural feature. The known literature fingerprints viz. MDL MACCS 166-bit keys, circular fingerprints, ECFP, FCF2, Unity have been applied to a wide range of applications including prediction of absorption, distribution, metabolism, excretion and toxicity properties.
Conventional fragment based descriptors capture information without considering neighboring functional group environment and are insensitive to the total environment of a molecule. The similarity coefficients typically yield high similarity values when the reference molecule has just a few bits set in its fingerprint. To overcome these shortcomings some researchers have suggested the use of multiple similarity coefficients for example, Tanimoto, Cosine, Hamming, Russell Rao etc. but it was found that there is no single combination which works best for each and every activity class. In an earlier work Jurs in Anal Chem, 1988, 60, 2700-2706. has reported Carbon-13 magnetic resonance spectra simulation of various classes of small compounds. It was noted that chemical shift values encode several descriptors like presence of primary, secondary and tertiary carbons in the molecule, axial and equatorial bonds in cyclic systems and other topological features.
Article titled “New approaches for NMR screening in drug discovery” in Drug Discovery Today: Technologies Vol. 1, No. 3 2004 Ce'sar Ferna'ndez et al. discloses NMR screening techniques applied to drug discovery.
Article titled “Electron density fingerprints (EDprints): virtual screening using assembled information of electron density” by Albert J Kooistra et al. in Journal of Chemical Information and Modeling (Impact Factor: 4.3). December 2010; 50(10):1772-80 discloses a method to encode properties related to the electron densities of molecules (calculated (1)H and (13)C NMR shifts and atomic partial charges) in molecular fingerprints (EDprints.
Article titled “New approaches for NMR screening in drug discovery” in Drug Discovery Today: Technologies Vol. 1, No. 3 2004 Ce'sar Ferna'rndez et al. discloses NMR screening techniques applied to drug discovery.
Article titled “Electron density fingerprints (EDprints): virtual screening using assembled information of electron density” by Albert J Kooistra et al. in Journal of Chemical Information and Modeling (Impact Factor: 4.3). December 2010; 50(10):1772-80 discloses a method to encode properties related to the electron densities of molecules (calculated (1)H and (13)C NMR shifts and atomic partial charges) in molecular fingerprints (EDprints.
A cursory review of the prior art indicates that there is still a need in the art to provide an efficient method for high throughput screening in drug discovery. Therefore, the present inventors have come up with a novel method to compute and apply the NMR chemical shift based binary fingerprints for high throughput screening in drug discovery.